• This subsystem streamlines tasks such as drone-based plant protection, rotary tillage, sowing, and harvesting, providing real-time quality monitoring, task delegation, operational tracking, automated irrigation, and pump station control.

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• It enables remote pump station operations, water level supervision, and fault alerts. By integrating people and data seamlessly, it ensures precise agricultural management.

• Based on the planting plan, the system develops agricultural plans for the farm, issues agricultural tasks, customizes farm staff roles, and displays pending agricultural tasks within authorized scopes. It records agricultural activities and provides feedback on task execution results.

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• Utilizing drone monitoring to collect crop growth information, monitoring the growth cycle of crops based on soil and historical climate data, and providing a basis for irrigation, fertilization, plant protection, harvesting, and other agricultural activities.

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• Providing analysis on terrain, seedling emergence rate, meteorology, soil moisture, soil fertility, weed, crop growth, yield, etc.

• Enabling accurate meteorological applications that involve viewing weather forecasts for upcoming days, accumulated temperature, and rainfall.

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• The system monitors data from small-scale agricultural meteorological stations, soil moisture using on-farm meters, issues moisture alerts, tracks insect occurrences with monitoring lamps, conducts real-time farm surveillance via high-definition cameras, and gathers crop growth data.

• The efficient management of agricultural inputs involves recording inventory and processing procedures such as storage, issuance, damage reporting, etc. This includes conducting inventory checks, setting expiration date reminders, and maintaining detailed records of product information.

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• By accurately managing inventory and consumption data, real-time access to precise inventory levels is enabled, supporting timely and informed decision-making for waste management.

• The low-altitude remote sensing subsystem is primarily designed for drone field inspections and supports the design of field inspection parameters. Timely feedback on abnormal points during inspections are facilitated by alert notifications, significantly enhancing the efficiency of field inspections.

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• Through AI and image analysis technology, field abnormalities are promptly identified and recognized, effectively guiding management personnel in addressing field anomalies.

• The subsystem extracts and consolidates data on crop growth, aerial inspections, ground patrols, farm machinery, drones, etc.

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• It allows users to apply ground patrol management, agricultural management, crop data management, and operation data management information, which further enables specific field-by-field agricultural management information recording and data analysis.

• Displaying information of agricultural machinery and plant protection drones monitoring, including machinery data, scheduling information, operation information, operating conditions, statistical information, etc., and networking and digitizing the agricultural machinery and IoT devices

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• Employing artificial intelligence (AI) and big data technologies to perform calculations, generate various prescription diagrams, and provide decision support data throughout the entire planting and harvesting process.

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• The AI identification model becomes more accurate as the learning samples increase.

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• Users can also choose specific plots, access plot details, and based on their selections, obtain expert-assisted planting schemes. These schemes consist of five components: planting scheme guidance (throughout the entire growth period), basic seedling analysis, plot information, growth records, etc.

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